a mathematical model of development of the green process in the textile industry: a case study of oyaz industrial company

The development of a green product process is a strategic approach to minimizing the effect of an organization’s supply chain on the environment while expanding its economic performance. in doing this, the dimensions focused on performance are essential in optimizing resource consumption and achieving sustainability concepts in an organizational context. for this purpose, in this study, a multi-objective mixed integer linear programming model is proposed with the aim of minimizing textile manufacturing time, transportation costs, and product inventory, as well as minimizing environmental effects in the green product development process. in this model, the constraints and parameters of the problem are certain and are solved using weighted sum methods, for which real data obtained from oyaz industrial group are used. by solving the model, an optimal combination for the values of the objective functions is obtained in combination and separately. finally, the effect of changing key parameters such as the maximum storage capacity of manufacturing centers on the decisions of the proposed model is examined through sensitivity analysis. this change of parameter is determined by consulting textile experts. according to the obtained results, changing the maximum storage capacity has a significant effect on fibers and cotton. also, in case of changing the capacity to the maximum possible value, it would have the greatest effect on the refiners. the least effect caused by changing the capacity of planting fields of environmentally friendly raw materials occurs when the capacity increases by 20,000. in this case, the least effect is made on the fields. also, the least effect of a change in capacity on inventory costs in the storage warehouse occurs when the capacity increases by 50,000. finally, the least effect of changing the capacity over time on the pollution rate occurs when the capacity is increased by 10,000 units.